R E S E A R C H A R T I C L E Open Access
Urinary angiotensinogen level is associated with potassium homeostasis and clinical outcome in patients with polycystic kidney disease: a prospective cohort study
Hyoungnae Kim1,2, Seohyun Park1, Jong Hyun Jhee3, Hae-Ryong Yun1, Jung Tak Park1, Seung Hyeok Han1, Joongyub Lee4, Soo Wan Kim5, Yeong Hoon Kim6, Yun Kyu Oh7, Shin-Wook Kang1, Kyu Hun Choi1, Tae-Hyun Yoo1* and Representing the KNOW-CKD Investigators Group
Abstract
Background:Guidelines for general hypertension treatment do not recommend the combined use of renin- angiotensin-aldosterone system (RAAS) inhibitors due to the risk of hyperkalemia. However, a recent clinical trial showed that polycystic kidney disease (PKD) patients had infrequent episodes of hyperkalemia despite receiving combined RAAS inhibitors. Because intrarenal RAAS is a main component for renal potassium handling, we further investigated the association between intrarenal RAAS activity and serum potassium level in patients with chronic kidney disease, particularly in PKD patients, and examined whether intrarenal RAAS activity has a prognostic role in patients with PKD.
Methods:A total of 1788 subjects from the KoreaN cohort study for Outcome in patients With Chronic Kidney Disease (KNOW-CKD) were enrolled in this study. Intrarenal RAAS activity was assessed by the measurement of urinary angiotensinogen (AGT). The primary outcome was the composite of all-cause mortality and renal function decline.
Results:Patients with PKD had a significantly lower serum potassium level in chronic kidney disease stages 1 to 3b than non-PKD patients. In logistic regression analysis, after adjusting for multiple confounders, PKD patients had a significantly lower risk of hyperkalemia than non-PKD patients. In multivariable linear regression analysis, the urinary AGT/creatinine (Cr) ratio was negatively correlated with the serum potassium level (β=−0.058,P= 0.017) and positively correlated with the transtubular potassium gradient (TTKG,β= 0.087,P= 0.001). In propensity score matching analysis, after matching factors associated with serum potassium and TTKG, PKD patients had a significantly higher TTKG (P= 0.021) despite a lower serum potassium level (P= 0.004). Additionally, the urinary AGT/Cr ratio was significantly higher in PKD patients than in non-PKD patients (P= 0.011). In 293 patients with PKD, high urinary AGT/Cr ratio was associated with increased risk of the composite outcome (hazard ratio 1.29; 95% confidence interval, 1.07–1.55;P= 0.007).
Conclusions:High activity of intrarenal RAAS is associated with increased urinary potassium excretion and low serum potassium level in patients with PKD. In addition, intrarenal RAAS activity can be a prognostic marker for mortality and renal function decline in these patients.
Keywords:Polycystic kidney disease, Angiotensinogen, Potassium
© The Author(s). 2019Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
* Correspondence:[email protected]
1Department of Internal Medicine, College of Medicine, Institute of Kidney Disease Research, Yonsei University, Seoul 03722, Republic of Korea Full list of author information is available at the end of the article
Background
Polycystic kidney disease (PKD) is a genetic disorder characterized by a progressively increasing number of fluid-filled cysts, distortion of the normal kidney struc- ture, and loss of renal function over a period of decades [1]. Early-onset hypertension is one of the key features in PKD, and up to 80% of patients are diagnosed as hav- ing hypertension before significant renal dysfunction [2].
In addition, hypertension is associated with a larger kid- ney volume, progression to end-stage renal disease, and cardiovascular mortality in patients with PKD [3–5].
Although the pathophysiologic mechanism of hyperten- sion has not been fully elucidated in PKD, it is generally accepted that the renin-angiotensin-aldosterone system (RAAS) plays a pivotal role [6, 7]. Moreover, RAAS is known to be one of the main contributors to the pro- gression of chronic kidney disease (CKD). Numerous clinical trials have demonstrated that RAAS inhibition by an angiotensin-converting enzyme inhibitor (ACEi) or angiotensin-II receptor blocker (ARB) prevents the progression of CKD [8–11]. Thus, it was expected that dual inhibition using an ACEi and ARB would be more effective in inhibiting the progression of CKD; however, three randomized controlled trials have failed to demon- strate this [12–14]. In contrast, these trials demonstrated that dual inhibition significantly increased the incidence of hyperkalemia and renal impairment. Furthermore, two of the trials involving dual RAAS inhibition in pa- tients with type 2 diabetes mellitus (DM) were termi- nated early because of an increased risk of hyperkalemia and acute kidney injury [13,14].
Recently, the effect of dual RAAS inhibition in pa- tients with PKD using an ACEi and ARB was evalu- ated in large randomized controlled trials (the HALT Progression of Polycystic Kidney Disease (HALT-PKD) studies) [15, 16]. These studies confirmed that redu- cing blood pressure is effective in reducing protein- uria and slowing the rate of total kidney volume increase. Interestingly, adverse events including hyper- kalemia and acute kidney injury were infrequent and not different between the dual and single RAAS in- hibition groups.
The potassium concentration in extracellular fluid is regulated within a narrow range by the kidney, the pri- mary organ of this homeostatic system. Augmented activ- ity of the RAAS increases sodium reabsorption in the kidney, which induces the electrochemical gradient for potassium to pass into the lumen in the distal convoluted tubule and collecting duct, enhancing potassium excretion [17]. Therefore in this study, we aimed to evaluate potas- sium regulation in patients with CKD due to PKD and other etiologies by analyzing the activity of the intrarenal RAAS and consequent tubular potassium secretion. Since urinary angiotensinogen (AGT) has been used as a
valuable biomarker for estimating the intrarenal RAAS in patients with CKD [18], we compared the relationship be- tween urinary AGT and serum potassium levels among patients with various etiologies of CKD. Furthermore, we investigated the role of urinary AGT as a prognostic marker in patients with PKD.
Methods
Study design and population
We utilized data from the KoreaN cohort study for Outcome in patients With Chronic Kidney Disease (KNOW-CKD), a nationwide, multi-center, prospect- ive cohort study to clarify the natural course, compli- cation profiles, and risk factors of Asian populations with CKD. The detailed design and methods of the study have been described previously [19] (ID no.
NCT01630486, http://www.clinicaltrials.gov). Briefly, 2341 individuals aged 20 to 75 years with CKD stages 1 to 5 without dialysis who voluntarily provided in- formed consent were recruited between 2011 and 2015 from 9 clinical centers. Exclusion criteria were as follows: 1) individuals unable or unwilling to give writ- ten consent, 2) individuals who previously received chronic dialysis or organ transplantation, 3) individ- uals with heart failure (New York Heart Association class III or IV), 4) individuals with liver cirrhosis (Child-Pugh class 2 or 3), 4) individuals with a past or current history of malignancy, 5) pregnant individuals, and 6) individuals with a single kidney due to trauma or kidney donation. After excluding 103 patients who did not meet the inclusion criteria or had missing data for isotope dilution mass spectrometry (IDMS)-cali- brated creatinine (Cr), 2238 participants were in- cluded. For this study, we additionally excluded 158 patients without data for urinary AGT levels. Further- more, to ensure correct calculation of the transtubular potassium gradient (TTKG), we excluded another 292 pa- tients with random urine sodium less than 25 mmol/L and those with urine osmolality less than the plasma osmolality [20]. Finally, 1788 patients were included in the analysis.
We first analyzed the relationship between urinary AGT and serum potassium level according to etiology of CKD in 1788 patients (Fig.1). In addition, we conducted a longitu- dinal analysis in 293 PKD patients to evaluate the impact of urinary AGT level on outcome in this group. This study was carried out in accordance with the Declaration of Helsinki, and the study protocol was approved by the re- spective institutional review boards of the participating centers, including Seoul National University Hospital, Yonsei University Severance Hospital, Kangbuk Samsung Medical Center, Seoul St. Mary’s Hospital, Gil Hospital, Eulji General Hospital, Chonnam National University Hospital, and Busan Paik Hospital.
Data collection
Baseline sociodemographic data were retrieved from the electronic data management system of the KNOW-CKD developed by the Seoul National University Medical Re- search Collaborating Center. Anthropometric measure- ments, including height and weight, were obtained at the baseline visit, and blood pressure was measured using an electronic sphygmomanometer by a trained nurse in the clinic. Blood and first-voided urine samples were sent to the central laboratory of the KNOW-CKD (Lab Genomics, Seongnam, Republic of Korea) by stand- ard protocol. The serum Cr level was measured by using the IDMS-traceable method, and estimated glomerular filtration rate (eGFR) was calculated with the CKD Epi- demiology Collaboration equation [21]. The urinary AGT level was measured by using an enzyme-linked im- munosorbent assay kit (IBL International GmBH, Ham- burg, Germany). Intra-assay and inter-assay coefficients of variation were less than 5.5 and 5.8%, respectively.
The TTKG was calculated by using the following for- mula: (urine potassium level/serum potassium level)/
(urine osmolality/serum osmolality) [22]. Hyperkalemia was defined as a serum potassium level greater than 5.0 mmol/L.
Clinical outcome
The primary outcome of this study was the composite of all-cause mortality and renal function decline. Renal
function decline was defined as a > 50% decline of the eGFR from baseline, doubling of the serum creatinine level, or the initiation of dialysis (hemodialysis or peri- toneal dialysis).
Statistical analyses
All subjects were categorized into 5 groups according to the etiology of CKD: diabetic nephropathy (DN), hyperten- sive nephrosclerosis (HTN), glomerulonephritis (GN), poly- cystic kidney disease (PKD), and unclassified. Continuous variables between groups were compared using one-way analysis of variance, and post-hoc analyses between groups were conducted with Bonferroni analysis. Nonparametric variables were compared using the Kruskal-Wallis test, and categorical variables were compared using the chi-square test. The risks of hyperkalemia among CKD patients grouped by etiology were compared using multivariable logistic regression analysis. To evaluate the relationship between the urinary AGT/Cr ratio and serum potassium level or TTKG, multivariable linear regression analyses were conducted, and the selection of covariables was done using the stepwise method. In addition, to minimize the effects of comorbidities, kidney function, and other labora- tory findings, propensity score matching (PSM) was used.
Propensity scores were estimated using logistic regression with the nearest neighbor technique without replacement, and a predefined caliper of 0.2 times the standard deviation.
The covariables shown to be associated with the serum Total 2238 patients who included in the KNOW-CKD study; CKD
stage 1-5 (pre-dialysis)
Excluded
-158 patients without data of urinary AGT levels - 292 patients with UNa< 25 mmol/L
2ndlongitudinal analysis : the relationship between urinary
AGT/Cr ratio and composite outcome in 293 PKD patients 1788 patients included for the study
1stcross-sectional analysis : the relationship between urinary AGT/Cr ratio and serum potassium levels (293 PKD patients vs. 1495
non-PKD patients) Fig. 1Flow chart for patient enrollment and analyses
potassium level and TTKG in multivariable linear regres- sion analysis were used for the matching. The PKD group was matched with the non-PKD group at a ratio of 1:1.
In these matched cohorts, comparisons between groups were conducted with the paired t-test, McNemar’s test, and Wilcoxon signed-rank test, as appropriate. Finally, we conducted multivariable Cox regression analysis to determine whether the AGT/Cr ratio was a prognostic factor of composite outcome in all 293 patients with PKD. We further categorized patients into 2 groups according to the median value of AGT/Cr ratio, and delineated the cumulative hazard of composite outcome in them using the multivariable Cox regression model.
Statistical significance was defined as P< 0.05. All statis- tical analyses were conducted by using SPSS software, ver- sion 23.0 with Essentials for R Plug-in (IBM Corporation, Armonk, NY, USA).
Results
Baseline characteristics
The baseline characteristics of patients according to the etiology of CKD are presented in Table 1. Pa- tients’ mean age was 54 ± 12.2 years, and 38.6% were women. The mean age was significantly lower in the PKD group than in the other groups. The prevalence rates of hypertension and DM were significantly lower in the PKD group than in the other groups (P< 0.001, all). The mean creatinine level and eGFR were 1.8 mg/dL and 50.1 mL/min/1.73 m2, respect- ively. The mean eGFR was significantly higher in the PKD group than in the other groups (P< 0.001, all).
The median urinary AGT/Cr ratio was 32.5, and it was not significantly different between the groups.
However, the mean serum potassium level in the PKD group was 4.4 ± 0.4 mmol/L, which was lower than that of the other groups (P< 0.001, all). In addition, the mean TTKG was significantly higher in the PKD group than in the other groups (P< 0.001, all). Fewer patients in the PKD group received any RAAS inhibition than the DN (P= 0.001) and GN (P< 0.001) groups, and fewer patients in the PKD group received dual RAAS inhibition than the others as well. The PKD group also had a smaller number of patients who received diuretics compared to the other groups (P< 0.001, all).
Risk of hyperkalemia among CKD groups
When we compared serum potassium levels for each CKD stage, the PKD group had a lower serum potassium level in CKD stages 1 to 3 than the non-PKD group (Fig. 2). The prevalence of hyperkalemia was also lower in the PKD group than in the other CKD groups up to CKD stage 3 (K > 5.0) and stage 4 (K > 5.5). In the other stages it is similar to all except DN (K > 5.0) or HTN
(K > 5.5) (Fig. 3). The lower prevalence of hyperkalemia in PKD was prominent in the early CKD stages, and attenuated with decline of renal function. In the multivari- able logistic regression analysis, we built up consecutive multi-step models. First, we adjusted for age, sex, history of DM, body mass index (BMI), and systolic blood pres- sure (SBP) in model 1, and found that the risk of hyperka- lemia was significantly lower in the PKD group than in the other CKD groups (Table 2). In model 2, we further adjusted for laboratory parameters including serum so- dium and urinary protein-to-creatinine ratio (UPCR);
use of anti-hypertensive medications (RAAS inhibition, diuretic, calcium channel blocker, and beta blocker) was then additionally adjusted for in model 3. Signifi- cantly lower risk of hyperkalemia in PKD was persistent in all models.
Urinary AGT/Cr ratio was correlated with the serum potassium level and TTKG
To evaluate the association between intrarenal RAAS activity and the serum potassium level, multivariable linear regression analyses were conducted (Table3). In these analyses, a history of DM, BMI, eGFR, total car- bon dioxide (CO2) level, serum albumin level, UPCR, urine osmolality, and use of diuretics were signifi- cantly correlated with the serum potassium level. In addition, the eGFR, total CO2 level, urine osmolality, age, sex, and Charlson comorbidity index (CCI) were associated with TTKG. The urinary AGT/Cr ratio was negatively correlated with the serum potassium level (β=−0.058, P= 0.017) and positively correlated with TTKG (β= 0.087,P= 0.001).
Values of urinary AGT/Cr ratio, serum potassium, and TTKG after PSM
To minimize the effect of confounders, PSM was per- formed. The matching was conducted with covariables, in- cluding age, sex, CCI, DM, BMI, eGFR, total CO2 level, serum albumin level, UPCR, urine osmolality, and use of diuretics, which were shown to be associated with the serum potassium level and TTKG. After matching patients in the PKD group with those in the non-PKD group, 196 patients remained in each group (Table4). In this matched cohort, patients in the PKD group had a significantly lower serum potassium level (P= 0.004) than the non-PKD group, whereas the serum sodium (P= 0.007) and chloride (P= 0.002) levels were higher in the PKD group than in the non-PKD group. Interestingly, the TTKG was significantly higher in the PKD group (P= 0.021), which means that urinary excretion of potassium was larger despite lower serum potassium levels in the PKD group. Moreover, the percentage of patients who received RAAS inhibition was not different between groups in the matched cohort,
Table1BaselinecharacteristicsofpatientsaccordingtoetiologyofCKD 5.VariablesTotalSubcohortp-value PKDDNHTNGNUnclassified Participants1788293429334618114 Age(years)54.0±12.247.0±10.959.5±9.2‡59.8±10.9‡50.1±12.1‡54.9±13.1‡<0.001 Female(n,%)690(38.6)148(50.5)127(29.6)‡93(27.8)‡273(44.2)49(43.0)<0.001 Hypertension(n,%)1723(96.4)255(87.0)424(98.8)‡334(100.0)‡600(97.1)‡110(96.5)‡<0.001 DM(n,%)628(35.1)12(4.1)429(100.0)‡63(18.9)‡57(9.2)‡67(58.8)‡<0.001 Currentsmoker(n,%)272(15.2)40(13.7)70(16.3)‡63(18.9)‡80(12.9)19(16.7)<0.001 BMI(kg/m2)24.7±3.423.6±3.125.4±3.3‡25.3±3.5‡24.2±3.325.5±4.0‡<0.001 Cardiovasculardisease(n,%) MI33(1.8)1(0.3)18(4.2)‡8(2.4)‡\5(0.8)1(0.9)<0.001 Stroke115(6.4)17(5.8)44(10.3)‡34(10.2)‡15(2.4)‡5(4.4)<0.001 PAD68(3.8)0(0.0)29(6.8)‡17(5.1)‡10(1.6)‡12(10.5)‡<0.001 SBP(mmHg)128.9±16.3128.7±13.3135.4±18.1‡128.9±15.4124.1±14.6‡131.0±19.5<0.001 DBP(mmHg)76.9±11.180.5±10.275.9±11.6‡77.8±11.4‡75.4±10.0‡77.5±13.4<0.001 CKDstages(n,%) Stage1204(11.4)76(25.9)12(2.8)9(2.7)91(14.7)16(14.0)<0.001 Stage2326(18.2)90(30.7)30(7.0)37(11.1)141(22.8)28(24.6) Stage3a326(18.2)43(14.7)65(15.2)77(23.1)127(20.6)14(12.3) Stage3b400(22.4)39(13.3)110(25.6)94(28.1)128(20.7)29(25.4) Stage4424(23.7)34(11.6)167(38.9)97(29.0)105(17.0)21(18.4) Stage5108(6.0)11(3.8)45(10.5)20(6.0)26(4.2)6(5.3) Creatinine(mg/dL)1.8±1.11.3±0.92.3±1.3‡2.0±1.2‡1.6±1.0‡1.6±0.9<0.001 eGFR(mL/min/1.73m2)50.1±29.968.1±34.335.3±20.4‡40.3±21.0‡56.2±30.3‡54.6±31.9‡<0.001 Hemoglobin(g/dL)12.8±2.013.3±1.811.7±1.9‡13.3±2.013.2±1.912.8±2.3<0.001 Albumin(g/dL)4.2±0.44.4±0.34.0±0.5‡4.3±0.34.1±0.4‡4.2±0.5‡<0.001 Calcium(mg/dL)9.1±0.59.3±0.58.9±0.6‡9.2±0.59.2±0.5‡9.2±0.5<0.001 Phosphorus(mg/dL)3.7±0.73.6±0.63.9±0.7‡3.6±0.63.6±0.63.8±0.6<0.001 Sodium(mmol/L)141.0±2.3141.1±2.2140.8±2.7141.1±2.3141.0±2.2140.4±2.40.037 Potassium(mmol/L)4.6±0.64.4±0.44.9±0.6‡4.6±0.6‡4.6±0.5‡4.7±0.6‡<0.001 Chloride(mmol/L)105.6±3.5105.6±2.9106.1±4.2105.6±3.5105.4±3.3105.1±3.70.011 TotalCO2(mmol/L)25.7±3.626.6±3.224.9±3.5‡25.5±3.6‡26.1±3.725.5±3.8<0.001 LDLcholesterol(mg/dL)96.5±31.0101.7±27.689.8±32.6‡93.8±30.1‡100.1±30.796.7±32.0<0.001 HDLcholesterol(mg/dL)49.1±15.254.6±14.043.1±13.2‡46.3±13.9‡51.6±15.6‡52.0±17.5<0.001
Table1BaselinecharacteristicsofpatientsaccordingtoetiologyofCKD(Continued) 5.VariablesTotalSubcohortp-value PKDDNHTNGNUnclassified UPCR(g/g)*0.5(0.1–1.5)0.8(0.5–2.0)1.6(0.4–3.8)‡0.3(0.1–0.8)‡0.6(0.3–1.6)‡0.6(0.2–1.6)‡<0.001 UACR(mg/g)*347.9(77.9-1080.5)35.2(13.3–121.7)1153.3‡(290.8-2642.9)175.2‡(24.9–535.1)483.7‡(216.2-1157.7)404.6‡(102.0-1127.3)<0.001 UrineAGT/Crratio(μg/g)*32.5(9.2-139.3)30.5(12.5–82.7)35.1(6.8–232.7)29.3(9.9–123.4)36.0(9.0–137.9)37.9(8.4–205.3)0.719 Urineosmolality(mOsm/kg)511.4±144.8516.7±156.2462.9±108.3‡504.8±129.7545.9±159.3‡513.3±142.6<0.001 TTKG6.4±2.47.2±2.85.6±2.1‡6.3±2.3‡6.5±2.4‡6.3±2.4‡<0.001 RAASblockade(n,%) Total1539(86.1)229(78.2)375(87.4)‡278(83.2)559(90.6)‡98(86.0)<0.001 ARBonly1344(75.2)215(73.4)325(75.8)254(76.0)462(74.9)88(77.2)0.91 ACEionly96(5.4)12(4.1)24(5.6)11(3.3)43(7.0)6(5.3)0.14 Dualblockade99(5.5)2(0.7)26(6.1)‡13(3.9)‡54(8.8)‡4(3.5)‡<0.001 RAASblockadedose(mg) ARB†68.5±32.268.9±25.273.7±34.366.6±32.266.1±31.267.0±36.00.01 ACEi¶8.9±5.38.9±5.310.6±6.114.1±10.410.2±5.18.9±5.30.051 Diuretics(n,%)577(32.3)32(10.9)245(57.1)‡115(34.4)‡151(24.5)‡34(29.8)‡<0.001 Diureticsdose(mg) Furosemide39.1±25.026.7±10.342.0±28.632.8±15.338.0±22.437.1±15.40.145 Torsemide6.5±7.8-4.8±2.26.7±2.64.8±1.814.5±20.00.161 Hydrochlorothiazide14.2±4.914.8±5.514.7±6.314.2±4.313.9±3.911.9±2.00.469 Spironolactone27.2±11.025.0±0.037.5±17.733.3±14.425.0±7.926.6±18.00.53 Calciumchannelblocker(n,%)750(42.0)101(34.5)240(55.9)‡169(50.6)‡184(29.8)56(49.1)‡<0.001 Betablocker(n,%)457(25.6)72(24.6)155(36.1)‡108(32.3)‡92(14.9)‡30(26.3)<0.001 *Dataareexpressedasmedianandinterquartileranges ‡Statisticallydifferent(P<0.05)whencomparedtoPKDgroup †AllotherdosesofARBsweresubstitutedfortheequivalentdoseoflosartan ¶AllotherdosesofACEinhibitorsweresubstitutedfortheequivalentdoseofenalapril Abbreviations:CKD,chronickidneydisease;DN,diabeticnephropathy;HTN,hypertensivenephropathy;GN,glomerulonephritis;PKD,polycystickidneydisease;DM,diabetesmellitus;BMI,bodymassindex;CAD, coronaryarterialdisease;MI,myocardialinfarction;PAD,peripheralarterialdisease;SBP,systolicbloodpressure;DBP,diastolicbloodpressure;eGFR,estimatedglomerularfiltrationrate;LDL,low-densitylipoprotein; HDL,high-densitylipoprotein;AGT,angiotensinogen;TTKG,transtubularpotassiumgradient;RAAS,renin-angiotensin-aldoteronesystem;ARB,angiotensinreceptorblocker;ACEi,angiotensinconverting enzymeinhibitor
however, patients in the PKD group had a significantly higher urinary AGT/Cr ratio (P= 0.011).
Urinary AGT/Cr ratio as a prognostic marker in patients with PKD
To examine the role of the urinary AGT/Cr ratio as a prognostic factor in the PKD group, we conducted multivariable Cox regression analyses (Table 5). Dur- ing the median follow-up of 4.6 years, 37 (12.6%) composite events (all-cause mortality and renal func- tion decline) occurred. After adjusting for multiple covariables, the urinary AGT/Cr ratio was a signifi- cant risk factor for the composite outcome (hazard ratio (HR) 1.29; 95% confidence interval (CI), 1.07–
1.55; P= 0.007). When we stratified patients into two groups according to the median value of the urinary AGT/Cr ratio of 30.5, those in the high urinary AGT/Cr ratio group had a significantly higher
cumulative hazard of the composite outcome (HR 2.26; 95% CI, 1.10–4.65; P= 0.026; Fig. 4).
Discussion
In this study, we demonstrated that the risk of hyper- kalemia was significantly lower in patients with PKD than in patients with other etiologies of CKD. In addition, the urinary AGT/Cr ratio was associated with TTKG as well as the serum potassium level. By using PSM analysis, we found that patients with PKD had a significantly lower serum potassium level and a higher urinary AGT/Cr ratio and TTKG when compared to patients without PKD. Therefore, it can be presumed that high activity of intrarenal RAAS causes larger urinary potassium excretion which leads to lower serum potassium levels in patients with PKD. Further- more, the urinary AGT/Cr ratio was a significant risk
0 10 20 30 40 50 60 70 80
Stage 1 Stage 2 Stage 3a Stage 3b Stage 4 Stage 5
)%(aimelakrepyh fo ecnelaverP
CKD stages
0 5 10 15 20 25 30 35 40 45
Stage 1 Stage 2 Stage 3a Stage 3b Stage 4 Stage 5 CKD stages
DN HTN GN PKD K > 5.0 mmol/L
A B
K > 5.5 mmol/L
Fig. 3Prevalence of hyperkalemia according to etiology of CKD in each CKD stage.aserum potassium level > 5.0 mmol/L, (b) serum potassium level > 5.5 mmol/L.
Fig. 2Serum potassium levels in each CKD stage. *P< 0.05
factor of all-cause mortality and decline in renal func- tion in patients with PKD.
It has been widely accepted that increased RAAS ac- tivity is a central physiologic mechanism for the devel- opment of hypertension in patients with PKD, and recent studies have focused further on its role in patients with PKD. Among several intrarenal RAAS components, the urinary AGT level has been shown to be correlated with the intrarenal activities of AGT and angiotensin II [23, 24]. In addition, the urinary AGT/Cr ratio was in- versely correlated with the eGFR and positively correlated with the height-adjusted total kidney volume in patients with PKD [25]. Kocyigit et al. also found that the urinary
AGT/Cr ratio was significantly associated with SBP [26], and reported that it was higher in hypertensive patients with PKD than healthy controls. A recent study by Salih et al. compared circulating and urinary RAAS compo- nents between patients with PKD and those with CKD but without PKD [27]; after adjusting for sex, eGFR, blood pressure, and RAAS inhibitor use between groups, the urinary AGT level and renin excretion were 5- to 6-fold higher in PKD than non-PKD patients, whereas circulat- ing levels were not different. This was consistent with the findings in our study. There have been several possible explanations to explain why patients with PKD have increased urinary RAAS activity. One is renin synthesis by the cyst epithelium and dilated tubules [28]. Another is that other components of RAAS, including AGT, angio- tensin converting enzyme (ACE), and angiotensin II can be produced within cysts and several parts of the tubules [29]. In addition, because renin and AGT are reabsorbed by a megalin-dependent pathway in the proximal tubule [30, 31], the functional defect in the proximal tubule in PKD can lead to increased concentration of tubular renin and angiotensinogen. Considering that ACE is abundant in the proximal tubular brush border, the highly concen- trated tubular renin and angiotensinogen can be easily converted to angiotensin I and II [32]. Moreover, aug- mented intrarenal RAAS activities are associated with chronic inflammation and fibrotic change in the kidney, which can lead to progressive renal injury [33, 34]. Ac- cordingly, previous studies showed that urinary AGT was associated with the development and progression of CKD [18,35]. In our study, we also showed that urinary AGT/
Cr ratio was correlated with decline in renal function and mortality in patients with PKD. To our knowledge, this is the first longitudinal study that has shown urinary AGT as a prognostic marker in patients with PKD.
Of note, we additionally found that the AGT/Cr ratio was negatively correlated with serum potassium level and positively correlated with TTKG. In our PSM ana- lysis, the TTKG was paradoxically elevated in patients Table 3Multivariate linear regression analyses for the
relationship between serum potassium, transtubular potassium gradient, and urine angiotensinogen-creatinine ratio
Variables Dependent variables
Serum potassium TTKG
β p-value β p-value
DM (vs. non-DM) 0.171 < 0.001 – –
BMI (kg/m2) −0.047 0.044 – –
eGFR (mL/min/1. 73m2) −0.315 < 0.001 0.157 < 0.001 Total CO2(mmol/L) −0.152 < 0.001 0.174 < 0.001
Serum albumin (g/dL) 0.066 0.019 – –
UPCR (g/g)* 0.120 < 0.001 – –
Urine AGT/Cr ratio (μg/g)* −0.058 0.017 0.087 0.001 Urine osmolality (mOsm/kg)* −0.056 0.046 0.118 < 0.001
Diuretics (vs. non-user) – –
Age (years) – – 0.104 < 0.001
Sex (vs. female) – – 0.139 < 0.001
Charlson comorbidity index – – −1.000 0.002
β: Standardized coefficient
*Variables are log transformed
Abbreviations: TTKG, trans-tubular potassium gradient; DM, diabetes mellitus;
BMI, body mass index; eGFR, estimated glomerular filtration; CO2, carbon dioxide; UPCR, urine protein-to-creatinine ratio;
AGT/Cr, angiotensinogen/creatinine
Table 2Logistic regression analysis for the risk of hyperkalemia according to etiology of CKD
CKD subcohort Unadjusted Model 1 Model 2 Model 3
OR (95% CI) p-value OR (95% CI) p-value OR (95% CI) p-value OR (95% CI) p-value
PKD (Reference) (Reference) (Reference) (Reference)
DN 9.52 (6.02–15.06) < 0.001 8.77 (4.74–16.24) < 0.001 4.65 (2.42–8.93) < 0.001 4.91 (2.54–9.50) < 0.001 HTN 3.42 (2.10–5.57) < 0.001 3.47 (2.07–5.83) < 0.001 2.54 (1.50–4.30) 0.001 2.57 (1.51–4.37) < 0.001 GN 2.79 (1.76–4.42) < 0.001 2.92 (1.82–4.66) < 0.001 1.70 (1.03–2.81) 0.038 1.82 (1.10–3.03) 0.02 Unclassified 4.57 (2.55–8.17) < 0.001 4.59 (2.44–8.65) < 0.001 2.86 (1.48–5.53) 0.002 2.95 (1.52–5.72) 0.001 Model 1: adjusted age, sex, history of DM, BMI, and SBP
Model 2: Model 1 + serum sodium and UPCR*
Model 3: Model 2 + use of RAAS blockade, diuretics, CCB, and beta blockers
*Data were log transformed
Abbreviations:CKDChronic kidney disease,ORodds ratio,CIConfidence interval,PKDPolycystic kidney disease,DNDiabetic nephropathy,HTNHypertensive nephrosclerosis,GN, glomerulonephritis; eGFR, estimated glomerular filtration rate;BMIBody mass index; SBP, systolic blood pressure; UPCR, urine protein-to- creatinine ratio; RAAS, renin-angiotensin-aldosterone system; CCB, calcium channel blocker
with PKD, even though it should be lowered when the serum potassium level is reduced. TTKG is positively as- sociated with mineralocorticoid activity [36]. Lai et al.
previously reported that the prevalence of primary aldos- teronism was 33% in patients with PKD, which was greater than that in the general population [37].
Therefore, augmented intrarenal activities of angiotensin II and aldosterone in PKD may lead to a lower serum potassium level than that in other etiologies of CKD. In the ONTARGET study, even though the mean creatinine level of the participants was within normal range, the combined use of telmisartan and ramipril was associated with a higher incidence of hyperkalemia [38]. In addition, combination treatment of losartan and lisino- pril for patients with DM in CKD stages 2 and 3 was stopped early in another study owing to safety concerns, including hyperkalemia [13]. The combination of a dir- ect renin inhibitor with other RAAS inhibitors also sig- nificantly increased the risk of hyperkalemia [14]. As a result, recent guidelines for hypertension do not recom- mend combined use of RAAS inhibitors in general hypertensive patients [39–41]. Furthermore, some re- searchers have been concerned about an increased risk of cancer with combination RAAS inhibitor therapy [42]. However, when confined to PKD patients, even in the study conducted for advanced PKD patients with an eGFR less than 60 mL/min/1.73 m2, episodes of hyperka- lemia were infrequent, and cancer risk was not increased [15]. Taking these results together, it can be suggested that patients with PKD may have a lower risk of Table 5Multivariable Cox regression analysis for composite
outcome in patients with PKD
Variables Hazard
ratio
95% confidence interval p-value
Age (year) 1.00 0.96–1.04 0.964
Sex (vs. female) 0.72 0.34–1.51 0.383
Baseline eGFR (mL/min/1. 73m2) 0.91 0.88–0.93 < 0.001
SBP (vs. < 130 mmHg) 2.02 1.03–3.97 0.042
BMI (kg/m2) 0.96 0.86–1.06 0.387
Use of RAAS blocker (vs. non-user) 1.29 0.42–3.95 0.655 Macroalbuminuria (vs. normo-
or microalbuminuria)
1.40 0.56–3.48 0.468
Urine AGT/Cr ratio (μg/g)a 1.29 1.07–1.55 0.007
aVariable was log transformed
Abbreviations: eGFR, estimated glomerular filtration rate; SBP, systolic blood pressure; BMI, body mass index; RAAS, renin-angiotensin-aldosterone;
AGT/Cr, angiotensinogen/creatinine
Table 4Propensity score matching analysis between the PKD and the non-PKD
Variables Before PSM After PSM
Non-PKD (N= 1495)
PKD
(N= 293) p-value Non-PKD
(N= 196)
PKD
(N= 196) p-value
Matched variables
Age (years) 55.3 ± 12.0 47.0 ± 10.9 < 0.001 49.6 ± 12.9 49.1 ± 11.1 0.66
Female (n, %) 542 (36.3) 148 (50.5) < 0.001 87 (44.4) 87 (44.4) > 0.999
Charlson comorbidity index 1.6 ± 1.3 1.4 ± 1.2 0.125 1.6 ± 1.3 1.4 ± 1.2 0.098
DM (n, %) 616 (41.2) 12 (4.1) < 0.001 22 (11.2) 11 (5.6) 0.068
BMI (kg/m2) 24.9 ± 3.4 23.6 ± 3.1 < 0.001 24.2 ± 3.7 24.1 ± 3.2 0.891
eGFR (mL/min/1. 73m2) 46.6 ± 27.6 68.1 ± 34.2 < 0.001 57.7 ± 29.7 59.1 ± 30.1 0.589
Total CO2(mmol/L) 25.6 ± 3.7 26.6 ± 3.2 < 0.001 26.4 ± 3.2 26.3 ± 3.2 0.924
Serum albumin (g/dL) 4.1 ± 0.4 4.4 ± 0.3 < 0.001 4.3 ± 0.3 4.4 ± 0.3 0.39
UPCR (g/g)a 0.6 (0.2–1.9) 0.1 (0.0–0.2) < 0.001 0.1 (0.0–0.4) 0.1 (0.0–0.3) 0.099
Urine osmolality (mOsm/kg)a 510.4 ± 142.5 516.7 ± 156.2 0.499 513.3 ± 148.0 514.2 ± 160.8 0.845
Diuretics (n, %) 545 (36.5) 32 (10.9) < 0.001 29 (14.8) 26 (13.3) 0.663
Matching results
Sodium (mmol/L) 140.9 ± 2.4 141.1 ± 2.2 0.206 140.9 ± 2.2 141.5 ± 2.0 0.007
Chloride (mmol/L) 105.6 ± 3.7 105.6 ± 3.0 0.716 105.1 ± 3.4 106.1 ± 3.0 0.002
Potassium (mmol/L) 4.7 ± 0.6 4.4 ± 0.4 < 0.001 4.6 ± 0.5 4.4 ± 0.5 0.004
TTKG 6.2 ± 2.3 7.2 ± 2.8 < 0.001 6.5 ± 2.6 7.1 ± 2.4 0.021
Urine AGT/Cr ratio (μg/g)a 33.6 (8.6–157.4) 30.5 (12.5–82.7) 0.627 17.7 (8.2–63.1) 30.5 (13.0–109.5) 0.011
RAAS blockade (n, %) 1310 (87.7) 229 (78.2) < 0.001 167 (85.2) 162 (82.7) 0.492
aData are expressed as median and interquartile range. Comparison was done by Mann-Whitney U test before matching, and Wilcoxon signed-rank test after matching
Abbreviations: PKD, polycystic kidney disease; PSM, propensity score matching; DM, diabetes mellitus; BMI, body mass index; eGFR, estimated glomerular filtration rate; CO2, carbon dioxide; UPCR, urine protein-to-creatinine ratio; TTKG, transtubular potassium gradient; AGT/Cr, angiotensinogen/creatinine
hyperkalemia than those with other etiologies of CKD.
Considering that the HALT-PKD investigators used a dose-adjustment protocol of RAAS inhibitors to achieve a specific blood pressure target, a higher degree of RAAS inhibition may be beneficial for attenuating the decline in renal function in PKD patients with a low risk of hyperkalemia.
Some limitations of this study should be discussed. First, we cannot confirm causality based on our cross-sectional analyses. However, with the vigorous adjustment of cov- ariables and diverse analyses in a large cohort, we found that patients with PKD had a higher AGT/Cr ratio and a lower serum potassium level than those with other etiolo- gies of CKD. Second, our data did not encompass any par- ameter of systemic RAAS activity. Systemic AGT is produced and released into circulation by the liver. Since the molecular weight of AGT is 52–64 kDa and it is nega- tively charged (similar to albumin), it cannot be filtered in the glomerulus of a healthy kidney [32]. However, in the case of proteinuric patients, systemic AGT can be filtered through the glomerular barrier; thus, the measured urin- ary excretion of AGT may partially reflect hepatic produc- tion and not purely intrarenally produced AGT.
Moreover, many experimental and clinical studies have re- ported that the urinary AGT/Cr ratio was positively corre- lated with proteinuria [18,23, 26, 35]. Therefore, Jang et
al. previously investigated this concern in patients with IgA nephropathy [43]. They reported that the intrarenal compartment, and not the systemic pool, was the main source of urinary AGT even in patients with overt pro- teinuria. In our study, PSM was performed mostly in pa- tients with microalbuminuria because the levels of UPCR were significantly lower in patients with PKD than in those with other etiologies of CKD. As the urinary AGT/
Cr ratio can be increased in patients with overt protein- uria, further studies with a wide range of proteinuria are warranted to evaluate the RAAS activity in various etiolo- gies of CKD with several components of the RAAS. Third, nutritional indices, including potassium intake, were not considered in our analyses. Low potassium intake is usu- ally recommended for patients with CKD to avoid hyper- kalemia in clinical practice, but it is also associated with high blood pressure and CKD progression [44, 45]. We did not include 24-h urinary potassium excretion in the analyses because it was measured only in 831 (46.5%) pa- tients. However, when we compared 24-h urinary potas- sium excretion after PSM, the levels were not different between the PKD and non-PKD groups (data not shown).
Conclusions
In conclusion, patients with PKD had a significantly lower serum potassium level than those with other
Fig. 4Cox proportional hazards regression curves for composite outcome in two groups of urinary AGT/Cr ratio. Curves were derived by adjustment of following covariables: age, sex, baseline eGFR, BMI, SBP (≥130 mmHg or not), presence of macro-albuminuria, use of RAAS blocker
